The present invention relates to the field of position determination, as it may occur in receivers in communication, multi-hop or ad-hoc networks and/or sensor networks, for example.
In wireless communication networks, position determination of individual network nodes often is possible in an inaccurate manner only. In decentralized networks, in particular, often co-operative localization is performed, wherein this may especially occur in so-called wireless sensor networks. Certain network nodes, also referred to as anchors or anchor nodes here, the position of which is known, here serve as supporting positions to determine a position of a receiver. For example, such anchor nodes may send out or communicate their positions, so that they may then be received by other mobile radio nodes. The received position information of the surrounding anchors may then be evaluated, wherein the position of a receiver can be calculated by maybe including other reception parameters, for example the reception field strength. What is problematic here, often only is the limited accuracy caused by effects in the radio field, for example.
One conventional method, for example, is the centroid method, also referred to as centroid determination in English. Here a network node receives, from surrounding transmitters, their transmitter positions and determines a geometrical centroid. Since there is no distance estimation in this method, the accuracy that can be achieved therewith is very limited only.
Another conventional method is the so-called weighted centroid method, also referred to as weighted centroid localization (WCL) in English. Here, a network node again receives position information from surrounding network or anchor nodes and determines a weighted centroid on the basis of the position information, i.e. the respective positions of the anchor nodes are weighted with the reception field strength at the network nodes, for example. This method has high inaccuracies particularly with irregular arrangements, because a group of nodes lying closely together obtains too high a weight.
This effect can be explained in greater detail on the basis of FIGS. 6a and 6b. FIG. 6a shows a network node M1, the position of which is to be determined. The anchor nodes A1-A4 are arranged around the network node M1. In the example of FIG. 6a, it is assumed that the anchor nodes A1-A4 transmit position information to the network node M1. Based on the reception field strength of the individual nodes A1-A4, as well as their positions, the network node M1 can determine its position on the basis of the weighted centroid method. The position determination of the node M1 in FIG. 6a works relatively accurately here, because the anchor nodes A1-A4 are arranged largely regularly around the network node M1.
FIG. 6b shows another example of a weighted centroid method. FIG. 6b again shows a network node M1, the position of which is to be determined. The true position of the network node M1 is indicated in FIG. 6b by way of a dashed circle. In FIG. 6b, the network node M1 is surrounded by six anchor nodes A1-A6. It can be seen in FIG. 6b that there is an accumulation of anchor nodes around the anchor node A4, since the anchor nodes A4 to A6 lie relatively closely together. According to the above explanation, the network node M1 receives the position information of the anchor nodes A1-A6 and forms a sum weighted with the respective reception powers, in order to determine a weighted centroid, in accordance with WCL. The position determined in this way is indicated in FIG. 6b as a solid circle, wherein it can be seen that the position is distorted by the accumulation of the anchor nodes in the upper right corner, so that now high inaccuracy occurs.
Another conventional method is the cellular position determination, wherein a cellular communication network is assumed here, also referred to as convex position estimation in English. Here, position determination takes place merely on the basis of a known cell identification (also referred to as cell ID in English), wherein this method has high inaccuracy, because no distance estimation whatsoever is taken into account, and the accuracy is determined by the size of a cell.
Another conventional method is triangulation, wherein a reception position is determined by trigonometric calculation of, for example, three or more transmitter positions. The distance estimates used are often too inaccurate to allow for exact triangulation, and hence for position determination.
Another conventional method is the so-called maximum likelihood multilateration, i.e. the maximation of a probability of a position estimation, wherein error minimization of a solution of a linear system of equations is used for position determination. This method is highly computation-intensive and necessitates a relatively dense network, which means that the respective anchor nodes must not be too far apart, because this method otherwise becomes error-prone.
Localization by way of WCL for location determination by means of received anchor positions, which are weighted with their reception field strengths (also referred to as RSSI=Received Signal Strength Indicator), as has been described on the basis of FIG. 6a, necessitates at least three non-collinear anchors for 2D position calculation. If additional redundant anchor positions are received from a network node, these can be used for the reduction of inaccuracies or variations of the RSSI values. For example, spurious quantities can be reduced by averaging RSSI values.
According to FIG. 6b, there may arise a problem of multiple weighting of anchor nodes lying closely together, which causes additional inaccuracies. Basically, WCL can be used because it has very little complexity and thus can be implemented well in embedded systems, but it has disadvantages with respect to the accuracy of the position determination, according to the above description.